A short presentation and then a demo:
- About Us
- Intro
- The Problem: Operationalizing Predictive Models
- Solutions
- Case Study: Iris Flower Predictor
- Demo
- Q & A
September 30, 2015
A short presentation and then a demo:
Common examples of data products:
- Loan/credit approval
- Recommendation systems (Movies, products, news feed)
- Qouting premiums; claims estimates - Churn reduction/ Customer retention
library(xtable) data(iris) print(xtable(head(iris, 5)), type = "html", include.rownames = F)
| Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
|---|---|---|---|---|
| 5.10 | 3.50 | 1.40 | 0.20 | setosa |
| 4.90 | 3.00 | 1.40 | 0.20 | setosa |
| 4.70 | 3.20 | 1.30 | 0.20 | setosa |
| 4.60 | 3.10 | 1.50 | 0.20 | setosa |
| 5.00 | 3.60 | 1.40 | 0.20 | setosa |